924 resultados para sequencing batch reactor


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Over 250 Mendelian traits and disorders, caused by rare alleles have been mapped in the canine genome. Although each disease is rare in the dog as a species, they are collectively common and have major impact on canine health. With SNP-based genotyping arrays, genome-wide association studies (GWAS) have proven to be a powerful method to map the genomic region of interest when 10-20 cases and 10-20 controls are available. However, to identify the genetic variant in associated regions, fine-mapping and targeted re-sequencing is required. Here we present a new approach using whole-genome sequencing (WGS) of a family trio without prior GWAS. As a proof-of-concept, we chose an autosomal recessive disease known as hereditary footpad hyperkeratosis (HFH) in Kromfohrl änder dogs. To our knowledge, this is the first time this family trio WGS-approach, has successfully been used to identify a genetic variant that perfectly segregates with a canine disorder. The sequencing of three Kromfohrl änder dogs from a family trio (an affected offspring and both its healthy parents) resulted in an average genome coverage of 9.2X per individual. After applying stringent filtering criteria for candidate causative coding variants, 527 single nucleotide variants (SNVs) and 15 indels were found to be homozygous in the affected offspring and heterozygous in the parents. Using the computer software packages ANNOVAR and SIFT to functionally annotate coding sequence differences and to predict their functional effect, resulted in seven candidate variants located in six different genes. Of these, only FAM83G:c155G>C (p.R52P) was found to be concordant in eight additional cases and 16 healthy Kromfohrl änder dogs.

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OBJECTIVE Intraarticular gadolinium-enhanced magnetic resonance arthrography (MRA) is commonly applied to characterize morphological disorders of the hip. However, the reproducibility of retrieving anatomic landmarks on MRA scans and their correlation with intraarticular pathologies is unknown. A precise mapping system for the exact localization of hip pathomorphologies with radial MRA sequences is lacking. Therefore, the purpose of the study was the establishment and validation of a reproducible mapping system for radial sequences of hip MRA. MATERIALS AND METHODS Sixty-nine consecutive intraarticular gadolinium-enhanced hip MRAs were evaluated. Radial sequencing consisted of 14 cuts orientated along the axis of the femoral neck. Three orthopedic surgeons read the radial sequences independently. Each MRI was read twice with a minimum interval of 7 days from the first reading. The intra- and inter-observer reliability of the mapping procedure was determined. RESULTS A clockwise system for hip MRA was established. The teardrop figure served to determine the 6 o'clock position of the acetabulum; the center of the greater trochanter served to determine the 12 o'clock position of the femoral head-neck junction. The intra- and inter-observer ICCs to retrieve the correct 6/12 o'clock positions were 0.906-0.996 and 0.978-0.988, respectively. CONCLUSIONS The established mapping system for radial sequences of hip joint MRA is reproducible and easy to perform.

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Familial acute myeloid leukemia is rare and linked to germline mutations in RUNX1, GATA2 or CCAAT/enhancer binding protein-α (CEBPA). We re-evaluated a large family with acute myeloid leukemia originally seen at NIH in 1969. We utilized whole-exome sequencing to study this family, and conducted in silico bioinformatics analysis, protein structural modeling and laboratory experiments to assess the impact of the identified CEBPA Q311P mutation. Unlike most previously identified germline mutations in CEBPA, which were N-terminal frameshift mutations, we identified a novel Q311P variant that was located in the C-terminal bZip domain of C/EBPα. Protein structural modeling suggested that the Q311P mutation alters the ability of the CEBPA dimer to bind DNA. Electrophoretic mobility shift assays showed that the Q311P mutant had attenuated binding to DNA, as predicted by the protein modeling. Consistent with these findings, we found that the Q311P mutation has reduced transactivation, consistent with a loss-of-function mutation. From 45 years of follow-up, we observed incomplete penetrance (46%) of CEBPA Q311P. This study of a large multi-generational pedigree reveals that a germline mutation in the C-terminal bZip domain can alter the ability of C/EBP-α to bind DNA and reduces transactivation, leading to acute myeloid leukemia.

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This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.

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This presentation was made at the Connecticut State Library Service Center, Willimantic, CT, April 14, 2009. It focused on digital capture workflows for both archival and derivative image creation using accepted current standards. Tools used were inexpensive by choice and focused towards the needs of small to mid-sized cultural heritage institutions who wish to begin digital capture in their own facilities.

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Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

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A clone of the primary Eco R1 family of human DNA sequences has been used as an indicator sequence for detecting alterations induced by a toxic agent. Specific clones of this family have been examined and compared to the consensus sequence to determine the normal variability of this family. Though variations were observed, data indicated that such clones can be used to study induced DNA modifications. This DNA was exposed to the toxic agent dimethyl sulfate under various conditions and a distinct pattern of aberrations was shown to occur. It is suggested that this approach be used to characterize patterns of damage induced by various agents in the ultimate development of a system capable of monitoring human genotoxic exposure. ^

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Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (

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My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status. Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We observe that accuracy improves along with the increasing sequencing depth. To model the overdispersion, we use the beta-binomial distribution with a new parameter indicating the dependency between overdispersion and sequencing depth. Our modified beta-binomial model performs better than the binomial or the pure beta-binomial model with a lower false discovery rate. Section 2: Although a number of methods have been proposed in order to accurately analyze differential RNA expression on the gene level, modeling on the base pair level is required. Here, we find that the overdispersion rate decreases as the sequencing depth increases on the base pair level. Also, we propose four models and compare them with each other. As expected, our beta binomial model with a dynamic overdispersion rate is shown to be superior. Section 3: We investigate biases in RNA-seq by exploring the measurement of the external control, spike-in RNA. This study is based on two datasets with spike-in controls obtained from a recent study. We observe an undiscovered bias in the measurement of the spike-in transcripts that arises from the influence of the sample transcripts in RNA-seq. Also, we find that this influence is related to the local sequence of the random hexamer that is used in priming. We suggest a model of the inequality between samples and to correct this type of bias. Section 4: The expression of a gene can be turned off when its promoter is highly methylated. Several studies have reported that a clear threshold effect exists in gene silencing that is mediated by DNA methylation. It is reasonable to assume the thresholds are specific for each gene. It is also intriguing to investigate genes that are largely controlled by DNA methylation. These genes are called “L-shaped” genes. We develop a method to determine the DNA methylation threshold and identify a new CIMP of BRCA. In conclusion, we provide a detailed understanding of the relationship between the overdispersion rate and sequencing depth. And we reveal a new bias in RNA-seq and provide a detailed understanding of the relationship between this new bias and the local sequence. Also we develop a powerful method to dichotomize methylation status and consequently we identify a new CIMP of breast cancer with a distinct classification of molecular characteristics and clinical features.

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Paracrine motogenic factors, including motility cytokines and extracellular matrix molecules secreted by normal cells, can stimulate metastatic cell invasion. For extracellular matrix molecules, both the intact molecules and the degradative products may exhibit these activities, which in some cases are not shared by the intact molecules. We found that human peritumoral and lung fibroblasts secrete motility-stimulating activity for several recently established human sarcoma cell strains. The motility of lung metastasis-derived human SYN-1 sarcoma cells was preferentially stimulated by human lung and peritumoral fibroblast motility-stimulating factors (FMSFs). FMSFs were nondialyzable, susceptible to trypsin, and sensitive to dithiothreitol. Cycloheximide inhibited accumulation of FMSF activity in conditioned medium; however, addition of cycloheximide to the migration assay did not significantly affect motility-stimulating activity. Purified hepatocyte growth factor/scatter factor (HGF/SF), rabbit anti-hHGF, and RT-PCR analysis of peritumoral and lung fibroblast HGF/SF mRNA expression indicated that FMSF activity was unrelated to HGF/SF. Partial purification of FMSF by gel exclusion chromatography revealed several peaks of activity, suggesting multiple FMSF molecules or complexes.^ We purified the fibroblast motility-stimulating factor from human lung fibroblast-conditioned medium to apparent homogeneity by sequential heparin affinity chromatography and DEAE anion exchange chromatography. Lysylendopeptidase C digestion of FMSF and sequencing of peptides purified by reverse phase HPLC after digestion identified it as an N-terminal fragment of human fibronectin. Purified FMSF stimulated predominantly chemotaxis but chemokinesis as well of SYN-1 sarcoma cells and was chemotactic for a variety of human sarcoma cells, including fibrosarcoma, leiomyosarcoma, liposarcoma, synovial sarcoma and neurofibrosarcoma cells. The motility-stimulating activity present in HLF-CM was completely eliminated by either neutralization or immunodepletion with a rabbit anti-human-fibronectin antibody, thus further confirming that the fibronectin fragment was the FMSF responsible for the motility stimulation of human soft tissue sarcoma cells. Since human soft tissue sarcomas have a distinctive hematogenous metastatic pattern (predominantly lung), FMSF may play a role in this process. ^

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The Annual Biochemical Engineering Symposium Series started in 1970 when Professors Larry E. Erickson (Kansas State University) and Peter J. Reilly (then with University of Nebraska-Lincoln) got together in Manhattan, KS along with their students for a half-day powwow and technical presentation by their students. Ever since then, it has been a forum for Biochemical Engineering students in the heartland of USA to present their research to their colleagues in the form of talks and posters. The institutions actively involved with this annual symposium include Colorado State University, Kansas State University, Iowa State University, University of Colorado, University of Kansas, University of Missouri-Columbia, and University of Oklahoma. The University of lowa and University of Nebraska-Lincoln have also participated in the conference in recent years. The host institutions for the different symposia have been: Kansas State University (1, 3, 5, 9, 12, 16, 20), Iowa State University (6, 7, 10, 13, 17, 22), University of Missouri-Columbia (8, 14, 19, 25), Colorado State University (II, 15, 21), University of Colorado (18, 24), University of Nebraska-Lincoln (2, 4), University of Oklahoma (23). The next symposium will be held at Kansas State University. Proceedings of the Symposium are edited by faculty of the host institution and include manuscripts written and submitted by the presenters (students). These often include works-in-progress and final publication usually takes place in refereed journals. ContentsPatrick C. Gilcrease and Vincent G. Murphy, Colorado State University. Use of 2,4,6-Trinitrotoluene (TNT) As A Nitrogen Source By A Pseudomonas florescens Species Under Aerobic Conditions. Marulidharan Narayanan, Lawrence C. Davis, and Larry E. Erickson, Kansas State University. Biodegradation Studies of Chlorinated Organic Pollutants in a Chamber in the Presence of Alfalfa Plants. S.K. Santharam, L.E. Erickson, and L.T. Fan, Kansas State University.Surfactant-Enhanced Remediation of a Non-Aqueous Phase Contaminant in Soil. Barry Vant-Hull, Larry Gold, and Robert H. Davis, University of Colorado.The Binding of T7 RNA Polymerase to Double-Stranded RNA. Jeffrey A. Kern and Robert H. Davis, University of Colorado.Improvement of RNA Transcription Yield Using a Fed-Batch Enzyme Reactor. G. Szakacs, M. Pecs, J. Sipocz, I. Kaszas, S.R. Deecker, J.C. Linden, R.P. Tengerdy, Colorado State University.Bioprocessing of Sweet Sorghum With In Situ Produced Enzymes. Brad Forlow and Matthias Nollert, University of Oklahoma.The Effect of Shear Stress ad P-selectin Site Density on the Rolling Velocity of White Blood Cells. Martin C. Heller and Theodore W. Randolph, University of Colorado.The Effects of Plyethylene Glycol and Dextran on the Lyophilization of Human Hemoglobin. LaToya S. Jones and Theodore W. Randolph, University of Colorado.Purification of Recombinant Hepatitis B Vaccine: Effect of Virus/Surfactant Interactions. Ching-Yuan Lee, Michael G. Sportiello, Stephen Cape, Sean Ferree, Paul Todd, Craig E. Kundrot, and Cindy Barnes, University of Colorado.Application of Osmotic Dewatering to the Crystallization of Oligonucleotides for Crystallography. Xueou Deng, L.E. Erickson, and D.Y.C. Fung, Kansas State University.Production of Protein-Rich Beverages from Cheese Whey and Soybean by rapid Hydration Hydrothermal Cooking. Pedro M. Coutinho, Michael K. Dowd, and Peter J. Reilly, Iowa State University.Automated Docking of Glucoamylase Substrates and Inhibitors. J. Johansson and R.K. Bajpai, University of Missouri.Adsorption of Albumin on Polymeric Microporous Membranes.